Appending to next row the result of math operation between three columns

Question

So, I have the following Pandas DataFrame where all values in third column (Ratio) are the same:

import pandas as pd 

df = pd.DataFrame([[2, 10, 0.5], 
                   [float('NaN'), 10, 0.5], 
                   [float('NaN'), 5, 0.5]], columns=['Col1', 'Col2', 'Ratio'])
╔══════╦══════╦═══════╗
║ Col1 ║ Col2 ║ Ratio ║
╠══════╬══════╬═══════╣
║ 2    ║   10 ║ 0.5   ║
║ NaN  ║   10 ║ 0.5   ║
║ NaN  ║    5 ║ 0.5   ║
╚══════╩══════╩═══════╝

I want to know if there is a way to multiply Col1 * Ratio and then the output of that product add it to Col2 and append the value to next row Col1 using a function provided by pandas.

Output example:

╔══════╦══════╦═══════╗
║ Col1 ║ Col2 ║ Ratio ║
╠══════╬══════╬═══════╣
║ 2    ║   10 ║ 0.5   ║
║ 11   ║   10 ║ 0.5   ║
║ 15.5 ║    5 ║ 0.5   ║
╚══════╩══════╩═══════╝

Answer 1

I think numba is way how working with loops here if performance is important:

from numba import jit

@jit(nopython=True)
def f(a, b, c):
    for i in range(1, a.shape[0]):
        a[i] = a[i-1] * c[i-1] + b[i-1]
    return a

df['Col1'] = f(df['Col1'].to_numpy(), df['Col2'].to_numpy(), df['Ratio'].to_numpy())
print (df)
   Col1  Col2  Ratio
0   2.0    10    0.5
1  11.0    10    0.5
2  15.5     5    0.5